AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Multifactor Dimensionality Reduction

Showing 1 to 10 of 50 articles

Clear Filters

Dimensionality reduction reveals fine-scale structure in the Japanese population with consequences for polygenic risk prediction.

Nature communications
The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on compl...

cnnAlpha: Protein disordered regions prediction by reduced amino acid alphabets and convolutional neural networks.

Proteins
Intrinsically disordered regions (IDR) play an important role in key biological processes and are closely related to human diseases. IDRs have great potential to serve as targets for drug discovery, most notably in disordered binding regions. Accurat...

Exploring gene-gene interaction in family-based data with an unsupervised machine learning method: EPISFA.

Genetic epidemiology
Gene-gene interaction (G × G) is thought to fill the gap between the estimated heritability of complex diseases and the limited genetic proportion explained by identified single-nucleotide polymorphisms. The current tools for exploring G × G were oft...

A data-driven dimensionality-reduction algorithm for the exploration of patterns in biomedical data.

Nature biomedical engineering
Dimensionality reduction is widely used in the visualization, compression, exploration and classification of data. Yet a generally applicable solution remains unavailable. Here, we report an accurate and broadly applicable data-driven algorithm for d...

Designing a hybrid dimension reduction for improving the performance of Amharic news document classification.

PloS one
The volume of Amharic digital documents has grown rapidly in recent years. As a result, automatic document categorization is highly essential. In this paper, we present a novel dimension reduction approach for improving classification accuracy by com...

Epistasis Analysis: Classification Through Machine Learning Methods.

Methods in molecular biology (Clifton, N.J.)
Complex disease is different from Mendelian disorders. Its development usually involves the interaction of multiple genes or the interaction between genes and the environment (i.e. epistasis). Although the high-throughput sequencing technologies for ...

A Belief Degree-Associated Fuzzy Multifactor Dimensionality Reduction Framework for Epistasis Detection.

Methods in molecular biology (Clifton, N.J.)
Epistasis is a challenge in prediction, classification, and suspicion of human genetic diseases. Many technologies, methods, and tools have been developed for epistasis detection. Multifactor dimensionality reduction (MDR) is the method commonly used...

Spatial rank-based multifactor dimensionality reduction to detect gene-gene interactions for multivariate phenotypes.

BMC bioinformatics
BACKGROUND: Identifying interaction effects between genes is one of the main tasks of genome-wide association studies aiming to shed light on the biological mechanisms underlying complex diseases. Multifactor dimensionality reduction (MDR) is a popul...

Interaction between maintenance variables of medical ultrasound scanners through multifactor dimensionality reduction.

Expert review of medical devices
BACKGROUND: Proper maintenance of electro-medical devices is crucial for the quality of care to patients and the economic performance of healthcare organizations. This research aims to identify the interaction between Ultrasound scanners (US) mainten...